Report NEP-ETS-2021-04-19

This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Jaqueson K. Galimberti issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon.

Other reports in NEP-ETS

The following items were announced in this report:

• Kadir Özen & Dilem Yıldırım, 2021. "Application of Bagging in Day-Ahead Electricity Price Forecasting and Factor Augmentation," ERC Working Papers 2101, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
• Joseph, Andreas & Kalamara, Eleni & Kapetanios, George & Potjagailo, Galina & Chakraborty, Chiranjit, 2021. "Forecasting UK inflation bottom up," Bank of England working papers 915, Bank of England, revised 27 Sep 2022.
• Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
• Christian M. Dahl & Emil N. S{o}rensen, 2021. "Time Series (re)sampling using Generative Adversarial Networks," Papers 2102.00208, arXiv.org.
• Xiao, Jiaqi & Juodis, Arturas & Karavias, Yiannis & Sarafidis, Vasilis, 2021. "Improved Tests for Granger Non-Causality in Panel Data," MPRA Paper 107180, University Library of Munich, Germany.
• Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
• Claudio Morana, 2021. "A new macro-financial condition index for the euro area," Working Papers 467, University of Milano-Bicocca, Department of Economics, revised Sep 2021.
• Gareth Liu-Evans, 2021. "Improving the Estimation and Predictions of Small Time Series Models," Working Papers 202106, University of Liverpool, Department of Economics.
• Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco, 2021. "Efficient and robust inference of models with occasionally binding constraints," JRC Working Papers in Economics and Finance 2021-03, Joint Research Centre, European Commission.
• Shalini Sharma & Víctor Elvira & Emilie Chouzenoux & Angshul Majumdar, 2021. "Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting," Post-Print hal-03184841, HAL.